Optimization Economic and Emissions of Hydro and Thermal Power Plants in 150 kV Systems Using the Dragonfly Algorithm

Bayu Setyo Wibowo, S. Handoko, H. Hermawan
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Abstract

Electricity is one of the energies required by daily living since the greater demand for electricity increases greenhouse emissions that create emission gases resulting in global climate change. The main portion of the output cost is fuel's cost to manufacture electrical energy in thermal turbines. The use of electrical energy is currently rising increasingly following the increasing population. The research aims to optimize hydro generation to minimize thermal generation expense and address economic problems and pollution from shipping. With 2016b using Matlab applications and the lambda iteration process, the analysis method uses the Dragonfly Algorithm method. The analysis found that the average cost of fuel consumption provided by the Dragonfly Algorithm method was IDR 151,164,418 per day with an emission of 917.40 tons per day, based on the simulation results the Dragonfly Algorithm in testing by considering the emission of 5 practical steps. Meanwhile, with the emission of 918,044 tonnes per day, the average cost of fuel consumption produced by the Lambda Iteration method is IDR 151,202,209 per day. Test results can enhance the fuel consumption cost of IDR 37,791 and emissions of 0.641 tons with the Dragonfly Algorithm process.
基于蜻蜓算法的150千伏水火电厂经济与排放优化
电力是日常生活所需的能源之一,因为电力需求的增加会增加温室气体的排放,从而产生导致全球气候变化的排放气体。输出成本的主要部分是在热轮机中制造电能的燃料成本。随着人口的增长,电能的使用量也在不断增加。该研究旨在优化水力发电,以最大限度地减少火力发电费用,并解决经济问题和航运污染问题。借助2016b的Matlab应用程序和lambda迭代过程,分析方法采用蜻蜓算法方法。分析发现,蜻蜓算法方法提供的平均燃料消耗成本为151,164,418印尼币/天,排放量为917.40吨/天,基于蜻蜓算法在测试中的模拟结果,考虑5个实际步骤的排放。同时,以每天918,044吨的排放量计算,Lambda迭代法产生的平均燃料消耗成本为每天151,202,209印尼盾。试验结果表明,采用蜻蜓算法流程可提高燃油消耗成本37,791印尼盾,排放量0.641吨。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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